Chapter 8 : Assessing Organizational Information (Data Warehouse)

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1. Describe the role and purpose of data warehouses and data marts in the organization

Data warehouses is a massive database (typically housed on a cluster of servers, or a mini or mainframe computer) serving as a centralized repository of all data generated by all departments and units of a large organization. Advanced data mining software is required to extract meaningful information from a data warehouse. The role of data warehouses are companies commonly use data warehouse to analyze trends over time. They might use it to view day-to-day operations, but it's primary function is often strategic planning based on long-terms data overviews. From such reports, companies make business models, forecasts and other projections. For example, Zalora.com build a warehouse that concentrates on sale. Using this warehouse, they can answer questions like "Who was our best customer for this item last year?" They also might want to know latest design of clothing that customers have been looking for. The purpose, of course, is to bring key sets of data about or used by the organization into one place. 

Bringing together so much data into a data warehouse makes analysis very difficult. To address this problem, organizations use what are called data marts. Data marts is a simple form of data warehouse that is focused on a single subject (or functional area), such as Sales, Finance, or Marketing. Data marts are often built and controlled by a single department within an organization. Given their single-subject focus, data marts usually draw data from only a few sources. The sources could be internal operation systems, a central data warehouse or external data. The purpose of data marts are designed to be made available to specific sets of users. For example, data about manufacturing can be put into a data mart and be made available to the production department. Human resource data can be put into another data mart and be provided to the human resources employees. This approach makes it easier for each group or constituency in the organization to access the data they need.


2. Explain the relationship between business intelligence and a data warehouse

Business Intelligence (BI) is a broad category of applications and technologies for gathering, storing, analyzing and providing access to data to help enterprise users make better business decisions. Its purposes  are acquire theoretical background in lectures and literature studies and obtain practical experience on (industrial) tools in practical exercises. A data warehouse is a repository for a company's historical data. Data warehouses can be physical or virtual, and they can be structurally relational, quasi relational, summarized, cubes, flat files or a combination of styles. Data warehousing is the set of technologies and techniques that you use to build and manage the data warehouse.

The relationship between Business Intelligence and Data Warehousing

The data warehouse gets its data from a variety of sources, including the extraction, transformation and loading (ETL) staging database, the online transaction processing (OLTP) transactional database, or even directly from external data sources. Then, depending on the data needed for a BI project, you can spin off multiple OLAP cubes (also called multidimensional databases) from the data warehouse. For example, a bank might analyze ATM transactions for behavior, time of a day, or queue information, whereas retail operation might perform a basket analysis on point of sales, POS transactions. On top of this underlying architecture, with the ability to tap into any or all of the data sources, is the BI software tools layer. This layer represents numerous BI packages that you can use to analyze data, generate reports and find information for making business decisions. You can even feed information into automated activities and other processes for additional analysis.